How long for forecast::auto.arima to work?

Question

I am working through some demo code that accompanied a medium post on high frequency time series forecasting using the forecast::auto.arima function. Whether in this application or when I have tried other datasets, I have never been able to get a result from this function - it does seem to stop calculating once I have executed it. Others have, obviously; so I'm asking how long you need to wait to get a result from the function.

Example

Data on hourly energy use can be downloaded from Kaggle.

Using that data:

library(tidyverse)
library(forecast)

duq_pc <- read.csv(file.choose(),stringsAsFactors = F)

duq_new <- duq_pc[duq_pc$Datetime >= '2013-01-01 00:00:00' & duq_pc$Datetime <= '2017-09-30 00:00:00',]

duq_train <- duq_new[duq_new$Datetime <= '2016-12-31',]
duq_test <- duq_new[duq_new$Datetime >= '2017-01-01',]
msts_power <- msts(duq_train$DUQ_MW, seasonal.periods = c(24,24*7,24*365.25), start = decimal_date(as.POSIXct("2013-01-01 00:00:00")))

#Dynamic Harmonic regression with Auto Arima

fourier_power <- auto.arima(msts_power, seasonal=FALSE, lambda=0,
                            xreg=fourier(msts_power, K=c(10,10,10)))

Very interested to hear whether this is something that I would need to leave running overnight or whether other people are getting results in minutes.

Answer 1

In my case, running your code and measuring the times in between, it took about 40 minutes to finish. For what it's worth, I launched the script on a computer with an AMD Ryzen 2700 Eight-Core Processor 3.20 GHZ, 16 GB of RAM.